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bayes net toolbox for
Bayes Net Toolbox For, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/bayes+net+toolbox+for/pmc12198876-11-5-3
Average 90 stars, based on 1 article reviews
Bayes Net Toolbox For, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/bayes+net+toolbox+for/pmc12198876-11-5-3
Average 90 stars, based on 1 article reviews
bayes net toolbox for - by Bioz Stars,
2026-09
90/100 stars
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other:Article Title: Data-driven estimation of building interior plans Article Snippet: Implementation of Bayesian networks in this work was achieved using the Article Title: Comprehensive review of Bayesian network applications in gastrointestinal cancers Article Snippet: BNT[ ] , MATLAB , Article Title: Effects of adapting to user pitch on rapport perception, behavior, and state with a social robotic learning companion Article Snippet: Social robots such as learning companions, therapeutic assistants, and tour guides are dependent on the challenging task of establishing a rapport with their users.. People rarely communicate with just words alone; facial expressions, gaze, gesture, and prosodic cues like tone of voice and speaking rate combine to help individuals express their words and convey emotion.. One way that individuals communicate a sense of connection with one another is entrainment, where interaction partners adapt their way of speaking, facial expressions, or gestures to each other; entrainment has been linked to trust, liking, and task success and is thought to be a vital phenomenon in how people build rapport. Article Title: Causal reasoning in Software Quality Assurance: A systematic review Article Snippet: [172] Article Title: Emotions recognition in an intelligent elearning environment Article Snippet: For the purpose of improving the quality in Elearning process and overcoming the limitations of the current online educational environments, we propose to take into consideration the emotional states of students during Elearning sessions.. Our objective is to ensure the ability of emotional intelligence: Emotion Recognition, in an eLearning environment.. Thus, we present an architecture of Emotionally Intelligent Elearning System (EIES). Article Title: A branch-and-cut approach to solve the Fault Diagnosis Problem with Lazy Spread and imperfect system information Article Snippet: This paper presents a new approach to solving the Fault Diagnosis Problem with Lazy Spread (FDPL) that arises in many fault-tolerant real-world systems with few opportunities for maintenance during their operations and significant failure interactions between the subsystems/components.. As opposed to cascading faults that spread to most of the system almost instantaneously, FDPL considers fault-resistant systems where the spread of failures is relatively slow (lazy), i.e., only a small fraction of the components are faulty at the time of inspection, and accurate diagnosis of the faulty components is of critical importance to restore system performance and stop further damage.. Introducing an extra level of difficulty, FDPL needs to be solved under imperfect (missing and wrong) system information in most real-world settings. Article Title: Detection of masses in digital breast tomosynthesis using complementary information of simulated projection. Article Snippet: Purpose: The purpose of this study is to develop a computer-aided detection system that combines the detection results in 3D digital breast tomosynthesis (DBT) volume and 2D simulated projection (synthesized image which is not provided by the vendor but generated from DBT volume in this study) to improve the accuracy of mass detection in DBT.. Methods: The 3D DBT volume has a problem of blurring in the out-of-focus plane because it is reconstructed from a limited number of projection view images acquired over a limited angular range.. To solve the problem, the simulated projection is generated by measuring the blurriness of voxels in the DBT volume and adopting conspicuity voxels. Article Title: An efficient Bayesian network structure learning algorithm based on structural information Article Snippet: Bayesian networks (BNs) are probabilistic graphical models regarded as some of the most compelling theoretical models in the field of representation and reasoning under uncertainty.. The search space of the model structure grows super-exponentially as the number of variables increases, which makes BN structure learning an NP-hard problem.. Evolutionary algorithm-based BN structure learning algorithms perform better than traditional methods. |